Lead Databricks Architect – Financial Services & Banking

Sutherland is seeking an experienced Lead Databricks Architect with deep domain expertise in the banking and financial services industry to drive the strategy, design, and implementation of our enterprise lakehouse platform.

In this role, you will bridge the gap between complex banking business requirements and cutting-edge data architecture. You will be responsible for building a secure, scalable, and highly performant Databricks lakehouse environment that powers critical banking applications, including regulatory reporting, risk management, fraud detection, customer analytics, and real-time transaction processing.

Key Responsibilities

Architecture & Platform Strategy

• Design and implement an enterprise-grade Databricks Lakehouse architecture leveraging Delta Lake, Unity Catalog, and Databricks SQL tailored for financial data models.
• Establish architectural patterns for high-throughput batch and real-time streaming data pipelines (e.g., Structured Streaming, Auto Loader) integrating core banking systems, payment gateways, and third-party data providers.
• Drive the migration strategy from legacy data warehouses (e.g., Teradata, Oracle, Snowflake, mainframe environments) to Databricks.

 
Security, Compliance & Governance

• Implement strict data security, enterprise access controls, and fine-grained permissions using Databricks Unity Catalog to comply with financial regulations (e.g., GDPR, SOX, PCI-DSS).
• Architect data masking, tokenization, and encryption strategies for Personally Identifiable Information (PII) and Sensitive Personal Data (SPD).
• Ensure full data lineage, auditing, and metadata management across multi-cloud or hybrid-cloud deployment environments (Azure).
Data Engineering & Performance Optimization

• Define best practices for PySpark, Delta Live Tables (DLT), and SQL optimization to maximize compute efficiency and reduce total cost of ownership (TCO).
• Establish CI/CD, DevOps, and MLOps automation frameworks for code deployment, data quality validation (e.g., Great Expectations), and model lifecycle management.
• Partner with Data Science, Quantitative Analytics, and BI teams to support advanced financial modeling, predictive risk analysis, and customer 360 initiatives.

 
Stakeholder & Domain Leadership

• Collaborate with business leaders, Chief Risk Officers (CROs), and compliance teams to align data platform capabilities with core banking business objectives.
Provide technical leadership, mentorship, and architecture governance to data engineering and analytics teams.

Function: Health Care Provider
Experience Level: Mid-Senior Level